{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0e1b14e7-7eb3-403c-b994-2d4c939d82b8",
   "metadata": {},
   "source": [
    "Chapter 25\n",
    "\n",
    "# 谱聚类\n",
    "Book_7《机器学习》 | 鸢尾花书：从加减乘除到机器学习"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "04027bae-d0f6-4f1f-b4a8-74ff642d6b38",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import cluster, datasets\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from itertools import cycle, islice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df6751b0-2d13-4c81-9a3e-65c44c51fb8b",
   "metadata": {},
   "source": [
    "## 生成数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9daba6fd-f236-4899-a549-6c1e38b660a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(0)\n",
    "\n",
    "n_samples = 500;\n",
    "# 样本数据的数量\n",
    "\n",
    "dataset = datasets.make_circles(n_samples=n_samples, factor=.5,noise=.05)\n",
    "# 生成环形数据\n",
    "\n",
    "X, y = dataset\n",
    "# X 特征数据，y 标签数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1f44e555-ac77-4dcb-9b7e-7f7a7ca29890",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = StandardScaler().fit_transform(X)\n",
    "# 标准化数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1230d654-1d1a-4d9a-9383-27218fc65789",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [-4.77193267e-02,  9.59982726e-01],\n",
       "       [-7.39158745e-01, -4.54301224e-01],\n",
       "       [-1.13125288e+00,  1.45411173e+00],\n",
       "       [ 7.71252660e-01, -5.26147849e-01],\n",
       "       [-4.02507344e-01,  1.90203806e+00],\n",
       "       [-1.15647699e+00,  1.31318263e+00],\n",
       "       [ 5.24235212e-01,  7.97241941e-01],\n",
       "       [ 1.69536462e+00, -4.46429961e-01],\n",
       "       [ 8.99571983e-01,  5.72494593e-01],\n",
       "       [ 1.03896111e+00, -1.44002839e+00],\n",
       "       [ 1.77347772e+00,  4.51103429e-01],\n",
       "       [-7.53503819e-01,  3.19200771e-01],\n",
       "       [ 3.07817572e-01, -1.89177510e+00],\n",
       "       [ 8.20467284e-01,  5.16601497e-02],\n",
       "       [-1.38872455e-01,  9.14790714e-01],\n",
       "       [ 1.70808277e-01, -1.86947765e+00],\n",
       "       [-1.99091477e+00,  4.61785529e-01],\n",
       "       [ 6.23776021e-01,  1.60670285e+00],\n",
       "       [-6.63986820e-01, -1.76052280e+00]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a57d31f-a5ee-4abb-bf00-343f67fbf94e",
   "metadata": {},
   "source": [
    "## 聚类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "37be5d17-403f-4dc6-a381-29d3245ee889",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\james\\anaconda3\\lib\\site-packages\\sklearn\\manifold\\_spectral_embedding.py:274: UserWarning: Graph is not fully connected, spectral embedding may not work as expected.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "spectral = cluster.SpectralClustering(\n",
    "    n_neighbors = 20,\n",
    "    assign_labels='discretize',\n",
    "    eigen_solver=\"arpack\",\n",
    "    affinity=\"nearest_neighbors\",\n",
    "    n_clusters=2)\n",
    "# 使用SpectralClustering算法对数据进行聚类\n",
    "\n",
    "y_pred = spectral.fit_predict(X)\n",
    "# 返回每个样本的聚类标签"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08ac834f-6b54-44aa-a446-89b485dc8f8f",
   "metadata": {},
   "source": [
    "## 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8384a046-f274-49ea-b1b4-ebc712d5d7e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "colors = np.array(list(islice(cycle(['#377eb8', '#ff7f00', '#4daf4a',\n",
    "                                     '#f781bf', '#a65628', '#984ea3',\n",
    "                                     '#999999', '#e41a1c', '#dede00']),\n",
    "                              int(max(y_pred) + 1))))\n",
    "\n",
    "plt.scatter(X[:, 0], X[:, 1], s=10, color=colors[y_pred])\n",
    "\n",
    "plt.xlim(-2.5, 2.5)\n",
    "plt.ylim(-2.5, 2.5)\n",
    "plt.xticks(())\n",
    "plt.yticks(())\n",
    "plt.axis('equal')\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
